ArticleEuropean heart journal. Digital health2023
Predicting left ventricular hypertrophy from the 12-lead electrocardiogram in the UK Biobank imaging study using machine learning.
Article in European heart journal. Digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 21 citations in OpenAlex.
- Deep learning to predict left ventricular hypertrophy from the electrocardiogram.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2026Article
- Automated estimation of computed tomography-derived left ventricular mass using sex-specific 12-lead ECG-based temporal convolutional network.European heart journal. Digital health · 2026Article
- Familial left ventricular noncompaction cardiomyopathy associated with the p.Asp461AsnOpen life sciences · 2026Article
- Circulating transthyretin with atrial morpho-functional phenotypes and atrial fibrillation risk, and the modifying role of BMI.BMC medicine · 2025Article
- Automated detection of non-physiological artifacts on ECG signal: UK Biobank and CRIC.Computers in biology and medicine · 2025Article
- Identification of hypertrophic cardiomyopathy on electrocardiographic images with deep learning.Nature cardiovascular research · 2025Article
- Association of biological aging acceleration transitions and burdens with incident cardiovascular disease: longitudinal insights from a national cohort study.BMC medicine · 2025Article
- Correlations Between Novel Adiposity Indices and Electrocardiographic Evidence of Left Ventricular Hypertrophy in Individuals with Arterial Hypertension.Journal of personalized medicine · 2025Article
- Identification of Hypertrophic Cardiomyopathy on Electrocardiographic Images with Deep Learning.medRxiv : the preprint server for health sciences · 2025Article
- Correlating Left Atrial Enlargement and Left Ventricular Hypertrophy on ECG With Echocardiography and Cardiac Magnetic Resonance Imaging.Journal of the American Heart Association · 2025Article
- Screening for Left Ventricular Hypertrophy Using Artificial Intelligence Algorithms Based on 12 Leads of the Electrocardiogram-Applicable in Clinical Practice?-Critical Literature Review with Meta-Analysis.Healthcare (Basel, Switzerland) · 2025Review
- AI-based integration of ECG biomarkers for assessing cardiac risk in type 2 diabetes mellitus with comorbid conditions for patient stratification.Frontiers in medicine · 2025Article
- Article
- Artificial intelligence-enhanced patient evaluation: bridging art and science.European heart journal · 2024Review
- Searching for the Best Machine Learning Algorithm for the Detection of Left Ventricular Hypertrophy from the ECG: A Review.Bioengineering (Basel, Switzerland) · 2024Review
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 3 countries.
Funding
Abstract
Aims: Left ventricular hypertrophy (LVH) is an established, independent predictor of cardiovascular disease. Indices derived from the electrocardiogram (ECG) have been used to infer the presence of LVH with limited sensitivity. This study aimed to classify LVH defined by cardiovascular magnetic resonance (CMR) imaging using the 12-lead ECG for cost-effective patient stratification. Methods and results: We extracted ECG biomarkers with a known physiological association with LVH from the 12-lead ECG of 37 534 participants in the UK Biobank imaging study. Classification models integrating ECG biomarkers and clinical variables were built using logistic regression, support vector machine (SVM) and random forest (RF). The dataset was split into 80% training and 20% test sets for performance evaluation. Ten-fold cross validation was applied with further validation testing performed by separating data based on UK Biobank imaging centres. QRS amplitude and blood pressure ( Conclusion: A combination of ECG biomarkers and clinical variables were able to predict LVH defined by CMR. Our findings provide support for the ECG as an inexpensive screening tool to risk stratify patients with LVH as a prelude to advanced imaging.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.